Background: The Iowa gambling task is a popular test for examining monetary decision behavior under uncertainty. According to Dunn et al. review article, the difficult-to-explain phenomenon of "prominent deck B" was revealed, namely that normal decision makers prefer bad final-outcome deck B to good final-outcome decks C or D. This phenomenon was demonstrated especially clearly by Wilder et al. and Toplak et al. The "prominent deck B" phenomenon is inconsistent with the basic assumption in the IGT; however, most IGT-related studies utilized the "summation" of bad decks A and B when presenting their data, thereby avoiding the problems associated with deck B.Methods: To verify the "prominent deck B" phenomenon, this study launched a two-stage simple version IGT, namely, an AACC and BBDD version, which possesses a balanced gain-loss structure between advantageous and disadvantageous decks and facilitates monitoring of participant preferences after the first 100 trials.Results: The experimental results suggested that the "prominent deck B" phenomenon exists in the IGT. Moreover, participants cannot suppress their preference for deck B under the uncertain condition, even during the second stage of the game. Although this result is incongruent with the basic assumption in IGT, an increasing number of studies are finding similar results. The results of the AACC and BBDD versions can be congruent with the decision literatures in terms of gain-loss frequency.Conclusion: Based on the experimental findings, participants can apply the "gain-stay, loss-shift" strategy to overcome situations involving uncertainty. This investigation found that the largest loss in the IGT did not inspire decision makers to avoid choosing bad deck B.

Ultra-wideband (UWB) radar is an important remote sensing tool of life detection or a non-contact monitor of the vital signals. By processing the received UWB pulse echoes reflected from the body, different signals corresponding to heart activity and breathing, corrupted by body motion and the environment noise etc., are wanted to be separated clearly. However, the heartbeat signal is so tiny that it is covered by breathing harmonics and clutters. At the same time, since the frequencies of the vital signals are very close, usually around 1 Hz, it is difficult to apply an ordinary frequency filter to separate them apart. This problem induces that the vital signal detection method, usually, only detects the large breath signal, not the heartbeat signal. To solve this problem, a novel method is provided, in this paper, to extract the heartbeat and the breath information simultaneously. The method uses the feature time index with the first valley-peak of the energy function of intrinsic mode functions (FVPIEF) calculated by pseudo bi-dimension ensemble empirical mode decomposition (PBDEEMD) method and extracts the vital signals by the ensemble empirical mode decomposition (EEMD). Both simulation and experiment results evidently show that the proposed FVPIEF Based Two-Layer EEMD method is effective for separating the small heartbeat signal from the large breath signal and significantly improves the evaluation of heart and breathing rates in both hold-breathing and breathing conditions.

Background: The Somatic Marker Hypothesis suggests that normal subjects are "foreseeable" and ventromedial prefrontal patients are "myopic" in making decisions, as the behavior shown in the Iowa Gambling Task. The present study questions previous findings because of the existing confounding between long-term outcome (expected value, EV) and gain-loss frequency variables in the Iowa Gambling Task (IGT). A newly and symmetrically designed gamble, namely the Soochow Gambling Task (SGT), with a high-contrast EV between bad (A, B) and good (C, D) decks, is conducted to clarify the issue about IGT confounding. Based on the prediction of EV (a basic assumption of IGT), participants should prefer to choose good decks C and D rather than bad decks A and B in SGT. In contrast, according to the prediction of gain-loss frequency, subjects should prefer the decks A and B because they possessed relatively the high-frequency gain.Methods: The present experiment was performed by 48 participants (24 males and 24 females). Most subjects are college students recruited from different schools. Each subject played the computer version SGT first and completed a questionnaire for identifying their final preference. The IGT experimental procedure was mostly followed to assure a similar condition of decision uncertainty.Results: The SGT experiment demonstrated that the prediction of gain-loss frequency is confirmed. Most subjects preferred to choose the bad decks A and B than good decks C and D. The learning curve and questionnaire data indicate that subjects can not "hunch" the EV throughout the game. Further analysis of the effect of previous choice demonstrated that immediate gain increases the probability to stay at the same deck.Conclusion: SGT provides a balanced structure to clarify the confounding inside IGT and demonstrates that gain-loss frequency rather than EV guides decision makers in these high-ambiguity gambles. Additionally, the choice behavior is mostly following the "gain-stay, lose-randomize" strategy to cope with the uncertain situation. As demonstrated in SGT, immediate gain can bring about a long-term loss under uncertainty. This empirical result may explain some shortsighted behaviors in real life.

Steady-state visual-evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have generated significant in terest due to their high information transfer rate (ITR). Due to the amplitude-frequency characteristic of the SSVEP, the flickering frequency of an SSVEP-based BCI is typically lower than 20 Hz to achieve a high SNR. However, a visual flicker with a flashing frequency below the critical flicker-fusion frequency often makes subjects feel flicker jerky and causes visual discomfort. This study presents a novel technique using high duty-cycle visual flicker to decrease user's visual discomfort. The proposed design uses LEDs flashing at 13.16 Hz, driven by flickering sequences consisting of repetitive stimulus cycles with a duration T (T = 76 ms). Each stimulus cycle included an ON state with a duration T_ON and an OFF state with a duration T_OFF (T = T_ON + T_OFF), and the duty cycle, defined as T_ONN/T, varied from 10.5% to 89.5%. This study also includes a questionnaire survey and analyzes the SSVEPs induced by different duty-cycle flickers. An 89.5% duty-cycle flicker, reported as a comfortable flicker, was adopted in a phase-tagged SSVEP system. Six subjects were asked to sequentially input a sequence of cursor commands with the 25.08-bits/min ITR.

Respiration is a crucial vital sign to indicate acidotic state of human body. In this paper, we have developed a Holo-Hilbert spectral analysis (HHSA)-based approach to detect subject’s respiration frequency from wrist photoplethysmogram (PPG) signals. The HHSA is a two-layer EMD architecture which first decomposes the original signal into intrinsic mode functions and then tries to find additive and multiplicative interactions among the participating components. The HHSA enables frequency-modulated (FM) and amplitude-modulated (AM) features of a signal can be comprehensively presented on a Holo-Hilbert spectrum (HHS). With the help of HHSA, subject’s respiration frequency can be identified on HHS by finding the AM frequency with the most prominent amplitude around the FM frequency of heart rate. The efficacy of the proposed method has been demonstrated in two designed experiments. In the first experiment, 75 subjects with ages ranged from 20–80 years old, and the difference between the detected results of proposed method and the readouts of transthoracic impedance plethysmography is 0.04 ± 0.96 breathes-per-minute (brm). In the second experiment, six subjects were requested to breathe at 6, 12, 18, 24 brm, following the pacing rhythms of a metronome. The difference between detected respiration rates and expected breathing rates is 0.01 ± 0.70 brm. The HHSA-based approach has manifested its capability to extract respiration-induced multiplicative component in PPG signal. It avoids the ambiguity of frequency representation in signal multiplication when using traditional additive decomposition methods.